Determining the genetic basis for variation in complex traits, including most human diseases, is a major goal in biology. Linkage disequilibrium (LD) now plays a central role - it is the basis for whole-genome population association mapping. LD is also key to understanding the origin and maintenance of genetic variation, as it describes how this variation is partitioned into haplotypes. This proposal investigates patterns and causes of LD and haplotype structure in Arabidopsis. Computational analyses of existing data will define haplotype structure and summarize LD patterns across the genome to identify significantly unusual regions. Fine-scale recombination rates will be directly measured and used to constrain haplotype evolution models. Computer simulations and statistical inference will assess the contribution that various population-level processes have in shaping LD patterns in order to interpret variation in the genome. Methods developed will have relevance to association mapping in economically important crops and will aid human complex disease association mapping studies and similar mapping and evolutionary studies in humans and other species. Developing computational and statistical tools will be key to interpret and utilize the data emerging from these projects.